A1 Journal article (refereed)
Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis (2022)

Zelinka, I., Diep, Q. B., Snášel, V., Das, S., Innocenti, G., Tesi, A., Schoen, F., & Kuznetsov, N. V. (2022). Impact of chaotic dynamics on the performance of metaheuristic optimization algorithms : An experimental analysis. Information Sciences, 587, 692-719. https://doi.org/10.1016/j.ins.2021.10.076

JYU authors or editors

Publication details

All authors or editors: Zelinka, Ivan; Diep, Quoc Bao; Snášel, Václav; Das, Swagatam; Innocenti, Giacomo; Tesi, Alberto; Schoen, Fabio; Kuznetsov, Nikolai V.

Journal or series: Information Sciences

ISSN: 0020-0255

eISSN: 1872-6291

Publication year: 2022

Volume: 587

Pages range: 692-719

Publisher: Elsevier

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1016/j.ins.2021.10.076

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/79478

Abstract

Random mechanisms including mutations are an internal part of evolutionary algorithms, which are based on the fundamental ideas of Darwin’s theory of evolution as well as Mendel’s theory of genetic heritage. In this paper, we debate whether pseudo-random processes are needed for evolutionary algorithms or whether deterministic chaos, which is not a random process, can be suitably used instead. Specifically, we compare the performance of 10 evolutionary algorithms driven by chaotic dynamics and pseudo-random number generators using chaotic processes as a comparative study. In this study, the logistic equation is employed for generating periodical sequences of different lengths, which are used in evolutionary algorithms instead of randomness. We suggest that, instead of pseudo-random number generators, a specific class of deterministic processes (based on deterministic chaos) can be used to improve the performance of evolutionary algorithms. Finally, based on our findings, we propose new research questions.

Keywords: chaos theory; evolutionary computation; swarm intelligence; algorithms; algorithmics

Free keywords: deterministic chaos; swarm intelligence; evolutionary algorithms; algorithm dynamics; algorithm performance

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2022

JUFO rating: 2